Risna Zubaidah
STIKES Arrahma Mandiri Indonesia

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PERCEPTION OF NET BENEFITS OF ELECTRONIC MEDICAL RECORDS AND ITS IMPACT ON THE EFFECTIVENESS OF POLY-CARE SERVICES IN HOSPITAL Mochammad Malik Ibrahim; Risna Zubaidah; Dhian Ika Prihananto
Jurnal Medicare Vol. 5 No. 3 (2026): JULY 2026 (INPRESS)
Publisher : Rena Cipta Mandiri

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.62354/jurnalmedicare.v5i3.465

Abstract

The digitization of medical records in hospitals was developed to support the quality and effectiveness of services through more systematic, rapid, and integrated patient data management. However, in its implementation, the utilization of this system has not fully achieved optimal results due to various technical and operational obstacles that still affect the smoothness of services and the level of benefits perceived by users. This study aims to analyze the relationship between the perceived net benefits of electronic medical records and the effectiveness of polyclinic services at Prof. Dr. Soekandar Regional General Hospital, Mojokerto Regency. The research was conducted using a quantitative approach using a cross-sectional analytical design. All 70 polyclinic staff were involved as respondents. Data were collected through questionnaires and tested for validity and reliability. The data were then analyzed descriptively and inferentially using the Spearman correlation test. The findings indicate that the perception of the benefits of EMR and the level of effectiveness of polyclinic services are mostly in the moderate category. Statistical testing confirmed a significant and positive correlation between the perceived benefits of the system and the effectiveness of services. This means that increasing the benefits of EMR tends to be followed by an increase in the effectiveness of polyclinic services. Therefore, optimizing system quality, strengthening information technology infrastructure, and improving user competency are strategic steps to maximize the utilization of EMR and improve health service performance.
Predictors of Turnover Intention among Nurses in Private Hospitals: A Cross-Sectional Study Using Logistic Regression Analysis Risna Zubaidah; Mochammad Malik Ibrahim
Journal Of Nursing Practice Vol. 9 No. 3 (2026): April
Publisher : Universitas STRADA Indonesia

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.30994/jnp.v9i3.1102

Abstract

Background: Turnover intention among nurses remains a critical workforce challenge, particularly in private hospitals where staffing instability directly affects service quality, patient safety, and organizational costs. Despite extensive research, evidence integrating multiple psychosocial work factors within a single multivariate model in the Indonesian private hospital context remains limited. This study addresses this gap by simultaneously examining key determinants of turnover intention and identifying the most influential predictors. Purpose: This study aimed to identify independent predictors associated with turnover intention among nurses in a private hospital setting. Methods: A cross-sectional study was conducted among nurses at a private hospital in Indonesia in 2025. A total of 70 respondents were selected using purposive sampling from a population of 81 nurses. Data were collected using a validated and reliable structured questionnaire. Turnover intention was dichotomized into high and low categories for logistic regression analysis. Data were analyzed using descriptive statistics, bivariate analysis (chi-square), and multivariate logistic regression. Although the sample size was relatively small, the number of predictors included in the final model was limited to ensure model stability. Results: Bivariate analysis showed that work motivation, work stress, burnout, work–life balance, job demands, and job satisfaction were significantly associated with turnover intention (p < 0.05). Multivariate logistic regression identified high work stress (POR = 31.62; 95% CI: 3.65–273.55; p = 0.002), high burnout (POR = 12.35; 95% CI: 1.78–85.58; p = 0.011), and low work motivation (POR = 9.02; 95% CI: 1.24–65.60; p = 0.030) as independent predictors of turnover intention. Conclusion: Turnover intention among nurses is primarily driven by high work stress, burnout, and low work motivation. These findings highlight the need for targeted organizational interventions focusing on stress management, burnout prevention, and motivation enhancement to improve nurse retention in private hospitals.